

'''simple docstring'''
_UpperCAmelCase  :		int  =		'''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

_UpperCAmelCase  :		Dict  =		[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
_UpperCAmelCase  :		Optional[int]  =		{
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}







'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCAmelCase									=   {
    """configuration_graphormer""": ["""GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GraphormerConfig"""],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase									=   [
					    """GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """GraphormerForGraphClassification""",
					    """GraphormerModel""",
					    """GraphormerPreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_graphormer import GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, GraphormerConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_graphormer import (
										    GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GraphormerForGraphClassification,
										    GraphormerModel,
										    GraphormerPreTrainedModel,
										)


else:
					import sys

					lowerCAmelCase									=   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



